Filter-Based Fading Channel Modeling

A channel simulator is an essential component in the development and accurate performance evaluation of wireless systems. A key technique for producing statistically accurate fading variates is to shape the flat spectrum of Gaussian variates using digital filters. This paper addresses various challenges when designing real and complex spectrum shaping filters with quantized coefficients for efficient realization of both isotropic and nonisotropic fading channels. An iterative algorithm for designing stable complex infinite impulse response (IIR) filters with fixed-point coefficients is presented. The performance of the proposed filter design algorithm is verified with 16-bit fixed-point simulations of two example fading filters

Frequency-domain Steiglitz-McBride method for least-squares IIR filter design, ARMA modeling, and periodogram smoothing

The classic Steiglitz-McBride (mode-1) time-domain algorithm for least-squares approximation of desired impulse responses for IIR digital filters or ARMA signal models is reformulated in the frequency domain to allow the direct least-squares approximation of either complex-valued or magnitude-only frequency responses, as well as power-density spectra, including periodograms. The resulting (stable) designs in the complex-valued case with both magnitude- and phase-response specifications can be either causal or noncausal, as appropriate to the phase, while the magnitude-only designs can always be made causal and minimum-phase. The periodogram models provide effective spectral smoothing without the need for averaging of data blocks, although averaging can be used, if desired, to reduce the computation. The filter coefficients can be either real- or complex-valued, corresponding to conjugate-symmetric or asymmetric frequency responses, respectively. © 2007 IEEE